Exploring predictors of welfare dependency 1, 3, and 5 years after mental health-related absence in danish municipalities between 2010 and 2012 using flexible machine learning modelling

Exploring predictors of welfare dependency 1, 3, and 5 years after mental health-related absence in danish municipalities between 2010 and 2012 using flexible machine learning modelling

Abstract Background Using XGBoost (XGB), this study demonstrates how flexible machine learning modelling can complement traditional statistical modelling (multinomial logistic regression) as a sensitivity analysis and predictive modelling tool in occupational health research. Design The study predic...

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Bibliographic Details
Main Author: Søren Skotte Bjerregaard
Format: Article
Language:English
Published: BMC 2023-02-01
Series:BMC Public Health
Subjects:
Welfare dependency
Return to work
XGboost
Machine learning
Shapley additive explanation
Common mental disorders
Online Access:https://doi.org/10.1186/s12889-023-15106-y

Internet

https://doi.org/10.1186/s12889-023-15106-y

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